Tag Archives: Willis Re

Underwriting Wildfire Takes Extra Care

This is part 2 in a series. You can find part 1 published here.

An increasingly volatile recipe of climate change and urbanization means that the past is no longer representative of the future when it comes to wildfire risk. Insurers can’t rely on previous wildfire seasons or events to inform future strategy. Just as every wildfire is unique, there simply is no one-size-fits-all approach to underwriting this risk. If you’re going to write wildfire risk in the U.S., and particularly in the West, then not only must you concede to assuming some level of risk but you must implement a more strategic approach. Savvy insurers know this, and that’s why they’re reaching out to solutions providers, brokers and data companies to help them develop a new game plan for a risk that’s 90% caused by humans and 100% variable. 

Back-to-back years of catastrophic wildfires raise the question: When will wildfires cease to be historic on an annual basis? According to GenRe, the severity of wildfire events is likely to continue. Its research reveals that it’s not so much the frequency of events (with the number of wildfires being fairly consistent since the 1980s), but the size of the event, with megafires an emerging trend: 

“Thinking of 2017 and 2018 as ‘1 in 20’ events may seem extreme; thinking of them as ‘1 in 5’ is almost too frightening to accept. No one knows the right answer, but we believe that long-term historical answers are unlikely to be the right ones.” — Ira Kaplan, GenRe 

So, how can insurers confidently underwrite wildfire risk when the cards seem stacked against them? Answer: By implementing a more innovative and strategic underwriting approach. 

My role as director of data products for Insurity’s SpatialKey solutions focuses on helping insurers explore new avenues to reduce wildfire risk and identify opportunities by applying smarter data and analytics. Our data partners continue to push the envelope by developing savvier ways to analyze risk by examining past behavior. For example, California’s megafires, including Tubbs, Thomas and of course the Camp Fire, which devasted the town of Paradise, have brought to light a few strategic considerations:

A single score is not the be-all-end-all

“It’s all about finding good risks in bad areas,” according to Clark Woodward, CEO and founder of RedZone, an innovative wildfire modeling company. “Wildfire is difficult to model because there are so many factors such as urbanization, a rapidly changing climate, increasingly intense fire behavior and the unpredictability of where fires ignite. This means insurers need to move away from a single score, which does not accurately encompass the complexities of fire risk. You’re going to be much more likely to be surprised if you are relying on a single number.”  

We’re seeing more of our partners, such as RedZone and Willis Re, bring data to market that tells a more complete story. For example, RedZone’s “correlated risk zones” data supports both underwriting and portfolio-level analysis by enabling risk analysts to identify communities or regions that may be many miles apart but could be affected by the same event. These regions, statistically, burn together even though they are separated by natural breaks (i.e. highways, ridgetops, rivers). The zones help insurers identify risk based on fire behavior and characteristics.

Reinsurance broker Willis Re is applying an innovative wildfire risk score underwriting methodology that also helps clients understand areas that are driving up probable maximum losses (PML) to help diversify portfolios and drive reinsurance costs down. This solution enables carrier clients to make more informed rating decisions while considering the hazard level of the new locations and the associated impact. As Vaughn Jensen, executive vice president at Willis Re, explains, “California’s recent wildfires illuminated that many carriers do not have a good handle on their wildfire risk, in no small part because existing industry models do not accurately represent the hazard.”

See also: Wildfire Season Off to Perilous Start

More data points need to be taken into consideration 

Layering HazardHub data, such as distance-to-fire-station and distance-to-hydrant, with another wildfire model can provide insurers with a more comprehensive understanding of wildfire risk, especially when visualized within a geospatial analytics solution that provides contextualization of the surrounding landscape. For example, visualizing wildfire risk in combination with data points that answer the following questions is critical to understanding the big picture: 

  • What’s the proximity to the nearest fire hydrant?
  • What’s the proximity to the nearest fire station? 
  • What’s the proximity/access to the nearest road(s)? 
  • Is there evidence of active tree clearing and mitigation efforts surrounding the structure(s)? 
  • What’s the loss type (i.e. direct, embers, smoke) and intensity?
  • What’s the construction type and year built (likeliness to burn)?

The above underwriting report includes critical fire station data from HazardHub along with the relative risk score of the peril itself from Willis Re. This combination of data points helps to contextualize and price risk in a single view.

Bringing it all together for a more strategic and informed view of wildfire risk

Multiple data points, and even multiple models, should be used collectively for more informed and strategic wildfire risk assessment at the point of underwriting. It’s imperative that wildfire risk isn’t assessed with a single model or single score, which is why I’m dedicated to facilitating a more open ecosystem where our P&C clients have access to multiple sources of expert data.

Equally important to leveraging new data sources is the ability to readily access them and use them to make informed underwriting decisions based on your risk appetite and in the context of your existing portfolio data. Making data easily accessible to decision-makers, along with enhanced analytics, will be the defining difference between companies that succeed with wildfire risk and those that fail.

Helping Insurers Get a Handle on Wildfire

“California is the lab for managing exposure to wildfire risk,” according to Lynn McChristian, a professor of risk management at Florida State University. If carriers and reinsurers can make it there, they can make it anywhere.

The past several years have seen a steep increase in the severity of wildfires, with the 2017 and 2018 seasons causing $24 billion in insured losses in California alone. Rates are climbing there, and coverage is dropping—there is clearly insufficient wildfire coverage to meet market demand, especially in high-risk, wildland-urbane interface (WUI) communities. 

These historic losses, combined with insufficient solutions for managing wildfire risk, mean insurers are trying to get a handle on their wildfire portfolio accumulations and gather perspective on relative risk. Simply put, the old way of doing things has been proven not to work—and insurers are demanding better. 

The flaw with historical wildfire risk management: Fires don’t burn in a circle

The California wildfires illuminated that many companies do not have clear best practices around managing wildfire risk, primarily because it has often been considered part of wider policy terms.

One solution is to limit accumulations between highly correlated areas of wildfire risk. Historically, insurers have looked at their concentrations of wildfire risk at the county level, along with using ring accumulations as a tool to assess risk. But fires don’t burn in a circle, and they don’t know postal code boundaries. Now, RedZone, a wildfire modeling company, has used millions of wildfire simulations to identify burn patterns across the landscape to create areas called “correlated risk zones.”

See also: Parametric Solution for Wildfire Risk

These zones are essentially regions that look completely separate but, statistically, burn together. They provide a logical and credible alternative by which to manage portfolio risk accumulations, alongside traditional loss modeling techniques. A more consistent approach to managing capacity can also improve risk-based pricing.

Solving a portfolio-scale problem requires changing the way we think

“Models have focused on risk at specific locations, but this is a portfolio-scale problem,” RedZone CEO and founder Clark Woodward says. 

The above screenshots show RedZone’s models for use in portfolio-level analysis. On the left is RedZone’s burn probability layer. When combined with the image on the right, which is RedZone’s hazard control zones, you can develop a firmer understanding of portfolio composition when it comes to accumulations and likeliness to burn. 

Accumulation analysis involves defining zones of correlated risk—where properties are likely to be damaged by the same event in the same year—and estimating the probable maximum loss (PML) within each zone. By evaluating accumulated wildfire risk, insurers can assess where additional properties may be insured with minimal increase in exposure to extreme losses. 

Reinsurance broker Willis Re has also brought to market a new methodology for wildfire underwriting and customer-specific portfolios. By helping carriers understand not only individual risk selection but geographic areas that are driving up their PMLs, Willis Re can, in turn, help them diversify their portfolios and drive down reinsurance costs.

Practical innovation that can be deployed now  

It’s taken a beat—and a harsh reality check—but better wildfire risk management strategies are now coming to fruition. Providers like RedZone, Willis Re and Insurity are working collaboratively to create solutions, like the correlated areas of risk discussed here, that provide better, more logical ways of managing wildfire accumulations.

This technology can be quickly deployed and implemented alongside traditional risk management strategies. This allows insurers to avoid disruption while employing a consistent approach to managing capacity across both underwriting and portfolio management and, ultimately, better serve and protect insureds against wildfire risk.

Shift in Capital for Reinsurers?

As more primary insurers use a formal risk appetite statement, their reinsurance buying habits have evolved, according to reinsurance brokerage Willis Re. And with reinsurance becoming a greater priority for many firms, there could be an opportunity for insurance-linked securities (ILS) to expand their global footprint.

Increased regulation across the insurance and reinsurance industry—underlined by the implementation of Solvency II in Europe and combined with a desire for greater risk and transactional transparency from investors—has caused a “fundamental shift in reinsurance purchasing,” Willis Re says.

In its recently published 2016 Global Risk Appetite Report, Willis Re highlights that reinsurance is moving up the priority list of global insurers. Purchasers are adopting different approaches, a trend that could result in the greater use of ILS capacity to optimize reinsurance programs.

The report says, “With rising regulatory and shareholder demands, increased pressure on insurer margins and a growing desire for a strong performance measurement framework, the dramatic shift towards risk quantification and management is clear.”

See Also: How to Understand Your Risk Appetite

At Artemis, we have previously discussed the notable changes in insurers reinsurance purchasing habits, particularly in light of the growing trend of centralized buying strategies to increase efficiency and drive potential organic growth opportunities, something that’s been limited in the softening landscape.

As some primary insurers look to retain more business, essentially keeping more risk on their books, the establishment of centralized reinsurance purchasing units has increased. Furthermore, a need for greater capital levels under Solvency II regulation has also seen some insurers retain more business, something that could result in greater demand for reinsurance.

Potential for increased reinsurance demand, the growing trend of centralized reinsurance purchasing and regulatory advances suggest ILS has an opportunity to capitalize on the changing habits of buyers and further grow their share of the overall reinsurance market pie.

The collateralized reinsurance market is one of the fastest-growing sub-sectors of the ILS space, and, as more primary players look to move their reinsurance purchasing in-house, it’s possible that collateralized reinsurance could feature more and more as insurers look to diversify their reinsurance placements with capital markets investor-backed capacity.

“As an industry, we’ve observed the broad shift around reinsurance purchasing in recent years with the increasing adoption of formal risk appetite statements,” said Tony Melia, Willis Re International CEO. “Those statements have proven essential to provide macro-level guidance to underwriting, global retention management and alignment of cession to wider strategies—linking ‘micro’ strategies to ‘macro’ targets.”

As insurers and reinsurers continue to adapt to new regulatory requirements, the softening re/insurance landscape and the resulting challenges, it’s expected that a variety of purchasing and distribution tools will be adopted and tested.

ILS capacity has been growing at an impressive rate absent any increase in demand for reinsurance protection from buyers, so it certainly wouldn’t be too surprising to us at Artemis if the market evolutions highlighted by Willis Re led to greater use of alternative risk transfer solutions to increase efficiency and diversify portfolios.

Are Market Cycles Finally Ending?

The property/casualty industry has been characterized by its market cycles since… well, forever. These cycles are multi-year affairs, where loss ratios rise and fall in step with rising and falling prices. In a hard market, as prices are rising, carriers are opportunistic and try to “make hay while the sun shines” – increasing prices wherever the market will let them. In a soft market, as prices are declining, carriers often face the opposite choice – how low will they let prices go before throwing in the towel and letting a lower-priced competitor take a good account?

Many assume that the market cycles are a result of prices moving in reaction to changes in loss ratio. For example, losses start trending up, so the market reacts with higher prices. But the market overreacts, increasing price too much, which results in very low loss ratios, increased competition and price decreases into a softening market. Lather, rinse, repeat.

But is that what’s really happening?

What’s Driving the Cycles?

Raj Bohra at Willis Re does great work every year looking at market cycles by line of business. In one of his recent studies, a graph of past workers’ compensation market cycles was particularly intriguing.


This is an aggregate view of the work comp industry results. The blue line is accident year loss ratio, 1987 to present. See the volatility? Loss ratio is bouncing up and down between 60% and 100%.

Now look at the red line. This is the price line. We see volatility in price, as well, and this makes sense. But what’s the driver here? Is price reacting to loss ratio, or are movements in loss ratio a result of changes in price?

To find the answer, look at the green line. This is the historic loss rate per dollar of payroll. Surprisingly, this line is totally flat from 1995 to the present. In other words, on an aggregate basis, there has been no fundamental change in loss rate for the past 20 years. All of the cycles in the market are the result of just one thing: price movement.

Unfortunately, it appears we have done this to ourselves.

Breaking the Cycle

As carriers move to more sophisticated pricing using predictive analytics, can we hope for an end to market cycles? Robert Hartwig, economist and president of the Insurance Information Institute, thinks so. “You’re not going to see the vast swings you did 10 or 15 years ago, where one year it’s up 30% and two years later it’s down 20%,” he says. The reason is that “pricing is basically stable…the industry has gotten just more educated about the risk that they’re pricing.”

In other words, Hartwig is telling us that more sophisticated pricing is putting an end to extreme market cycles.

The “what goes up must come down” mentality of market cycles is becoming obsolete. We see now that market cycles are fed by pricing inefficiency, and more carriers are making pricing decisions based on individual risks, rather than reacting to broader market trends. Of course, when we use the terms “sophisticated pricing” and “individual risk,” what we’re really talking about is the effective use of predictive analytics in risk selection and pricing.

Predictive Analytics – Opportunity and Vulnerability in the Cycle

Market cycles aren’t going to ever truly die. There will still be shock industry events, or changes in trends that will drive price changes. In “the old days,” these were the catalysts that got the pendulum to start swinging.

With the move to increased usage of predictive analytics, these events will expose the winners and losers when it comes to pricing sophistication. When carriers know what they insure, they can make the rational pricing decisions at the account level, regardless of the price direction in the larger market. In a hard market, when prices are rising, they accumulate the best new business by (correctly) offering them quotes below the market. In a soft market, when prices are declining, they will shed the worst renewal business to their naïve competitors, which are unwittingly offering up unprofitable quotes.


Surprisingly, for carriers using predictive analytics, market cycles present an opportunity to increase profitability, regardless of cycle direction. For the unfortunate carriers not using predictive analytics, the onset of each new cycle phase presents a new threat to portfolio profitability.

Simply accepting that profitability will wax and wane with market cycles isn’t keeping up with the times. Though the length and intensity may change, markets will continue to cycle. Sophisticated carriers know that these cycles present not a threat to profits, but new opportunities for differentiation. Modern approaches to policy acquisition and retention are much more focused on individual risk pricing and selection that incorporate data analytics. The good news is that these data-driven carriers are much more in control of their own destiny, and less subject to market fluctuations as a result.